Objective: Trajectories of physiomarkers over time can be useful to define phenotypes of disease progression and as predictors of clinical outcomes. The aim of this study was to identify phenotypes of the time course of late-onset sepsis in premature infants in Neonatal Intensive Care Units.
Methods: We examined the trajectories of a validated continuous physiomarker, abnormal heart rate characteristics, using functional data analysis and clustering techniques.
Participants: We analyzed continuous heart rate characteristics data from 2989 very low birth weight infants (<1500 grams) from nine NICUs from 2004-2010.
Result: Despite the relative homogeneity of the patients, we found extreme variability in the physiomarker trajectories. We identified phenotypes that were indicative of seven and 30 day mortality beyond that predicted by individual heart rate characteristics values or baseline demographic information.
Conclusion: Time courses of a heart rate characteristics physiomarker reveal snapshots of illness patterns, some of which were more deadly than others.
Keywords: Clinical Phenotypes; Continuous Monitoring; Functional Data Analysis; Predictive Modeling.
© The Author(s) 2020.